The UK Medical Research Council’s widely used guidance for developing and evaluating complex interventions has been replaced by a new framework, commissioned jointly by the Medical Research Council and the National Institute for Health Research, which takes account of recent developments in theory and methods and the need to maximise the efficiency, use, and impact of research.

Background The Medical Research Council published the second edition of its framework in 2006 on developing and evaluating complex interventions. Since then, there have been considerable developments in the field of complex intervention research. The objective of this project was to update the framework in the light of these developments. The framework aims to help research teams prioritise research questions and design, and conduct research with an appropriate choice of methods, rather than to provide detailed guidance on the use of specific methods. Methods There were four stages to the update: (1) gap analysis to identify developments in the methods and practice since the previous framework was published; (2) an expert workshop of 36 participants to discuss the topics identified in the gap analysis; (3) an open consultation process to seek comments on a first draft of the new framework; and (4) findings from the previous stages were used to redraft the framework, and final expert review was obtained. The process was overseen by a Scientific Advisory Group representing the range of relevant National Institute for Health Research and Medical Research Council research investments. Results Key changes to the previous framework include (1) an updated definition of complex interventions, highlighting the dynamic relationship between the intervention and its context; (2) an emphasis on the use of diverse research perspectives: efficacy, effectiveness, theory-based and systems perspectives; (3) a focus on the usefulness of evidence as the basis for determining research perspective and questions; (4) an increased focus on interventions developed outside research teams, for example changes in policy or health services delivery; and (5) the identification of six ‘core elements’ that should guide all phases of complex intervention research: consider context; develop, refine and test programme theory; engage stakeholders; identify key uncertainties; refine the intervention; and economic considerations. We divide the research process into four phases: development, feasibility, evaluation and implementation. For each phase we provide a concise summary of recent developments, key points to address and signposts to further reading. We also present case studies to illustrate the points being made throughout. Limitations The framework aims to help research teams prioritise research questions and design and conduct research with an appropriate choice of methods, rather than to provide detailed guidance on the use of specific methods. In many of the areas of innovation that we highlight, such as the use of systems approaches, there are still only a few practical examples. We refer to more specific and detailed guidance where available and note where promising approaches require further development. Conclusions This new framework incorporates developments in complex intervention research published since the previous edition was written in 2006. As well as taking account of established practice and recent refinements, we draw attention to new approaches and place greater emphasis on economic considerations in complex intervention research. We have introduced a new emphasis on the importance of context and the value of understanding interventions as ‘events in systems’ that produce effects through interactions with features of the contexts in which they are implemented. The framework adopts a pluralist approach, encouraging researchers and research funders to adopt diverse research perspectives and to select research questions and methods pragmatically, with the aim of providing evidence that is useful to decision-makers. Future work We call for further work to develop relevant methods and provide examples in practice. The use of this framework should be monitored and the move should be made to a more fluid resource in the future, for example a web-based format that can be frequently updated to incorporate new material and links to emerging resources. Funding This project was jointly funded by the Medical Research Council (MRC) and the National Institute for Health Research (Department of Health and Social Care 73514).

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Objective To compare the use and effect of a computer based information system for cancer patients that is personalised using each patient's medical record with a system providing only general information and with information provided in booklets. Design Randomised trial with three groups. Data collected at start of radiotherapy, one week later (when information provided), three weeks later, and three months later. Participants 525 patients started radical radiotherapy; 438 completed follow up. Interventions Two groups were offered information via computer (personalised or general information, or both) with open access to computer thereafter; the third group was offered a selection of information booklets. Outcomes Patients' views and preferences, use of computer and information, and psychological status; doctors' perceptions; cost of interventions. Results More patients offered the personalised information said that they had learnt something new, thought the information was relevant, used the computer again, and showed their computer printouts to others. There were no major differences in doctors' perceptions of patients. More of the general computer group were anxious at three months. With an electronic patient record system, in the long run the personalised information system would cost no more than the general system. Full access to booklets cost twice as much as the general system. Conclusions Patients preferred computer systems that provided information from their medical records to systems that just provided general information. This has implications for the design and implementation of electronic patient record systems and reliance on general sources of patient information.

Two hundred and seven male members of South Australian representative squads in 18 sports (mean +/- s = 24.2 +/- 4.7 years) were tested in order to provide descriptive data on relative body fat (% BF), develop a population specific equation and cross-validate existing equations. Measurements were taken of 10 circumferences, 2 diameters and 8 skinfolds; body density (BD) was measured by underwater weighing with the residual volume (RV) being determined by He dilution. The overall mean BD was 1.0761 g X cm-3 (s = 0.0085 g X cm-3; range = 1.0465-1.0968 g X cm-3) which corresponded to 10.0% BF according to Siri (s = 3.7%; range = 1.3-23.0%). The games players (n = 129) registered an overall mean of 10.3% BF (s = 3.7%; range = 2.2-23.0%). There were significant differences (p less than 0.05) for % BF between the lacrosse players (mean = 12.3%) an both the Australian Rules footballers (mean = 8.0%) and track and field athletes (mean = 8.7%). A stepwise multiple regression on 185 subjects yielded the following equation, which had an R of 0.787: BD = 1.078865-0.000419 (sigma abdominal, medial calf, front thigh and juxta-nipple skinfolds in mm) +0.000948 (neck circumference in cm) -0.000266 (age in decimal years) -0.000564 (ankle circumference in cm). Only those predictors which resulted in a significantly increased correlation (p less than or equal to 0.05) were included. The standard error of estimate of 0.00537 g X cm-3 was equivalent to 2.3% BF at the mean. This equation was satisfactorily cross-validated against the BD of a separate sample (n = 22) from the same population. However, cross-validation of 11 previously published equations indicated that they have limited applicability to State representative sportsmen.